Actual source code: sfcuda.cu
petsc-3.14.1 2020-11-03
1: #include <../src/vec/is/sf/impls/basic/sfpack.h>
2: #include <cuda_runtime.h>
3: #include <petsccublas.h>
5: /* Map a thread id to an index in root/leaf space through a series of 3D subdomains. See PetscSFPackOpt. */
6: __device__ static inline PetscInt MapTidToIndex(const PetscInt *opt,PetscInt tid)
7: {
8: PetscInt i,j,k,m,n,r;
9: const PetscInt *offset,*start,*dx,*dy,*X,*Y;
11: n = opt[0];
12: offset = opt + 1;
13: start = opt + n + 2;
14: dx = opt + 2*n + 2;
15: dy = opt + 3*n + 2;
16: X = opt + 5*n + 2;
17: Y = opt + 6*n + 2;
18: for (r=0; r<n; r++) {if (tid < offset[r+1]) break;}
19: m = (tid - offset[r]);
20: k = m/(dx[r]*dy[r]);
21: j = (m - k*dx[r]*dy[r])/dx[r];
22: i = m - k*dx[r]*dy[r] - j*dx[r];
24: return (start[r] + k*X[r]*Y[r] + j*X[r] + i);
25: }
27: /*====================================================================================*/
28: /* Templated CUDA kernels for pack/unpack. The Op can be regular or atomic */
29: /*====================================================================================*/
31: /* Suppose user calls PetscSFReduce(sf,unit,...) and <unit> is an MPI data type made of 16 PetscReals, then
32: <Type> is PetscReal, which is the primitive type we operate on.
33: <bs> is 16, which says <unit> contains 16 primitive types.
34: <BS> is 8, which is the maximal SIMD width we will try to vectorize operations on <unit>.
35: <EQ> is 0, which is (bs == BS ? 1 : 0)
37: If instead, <unit> has 8 PetscReals, then bs=8, BS=8, EQ=1, rendering MBS below to a compile time constant.
38: For the common case in VecScatter, bs=1, BS=1, EQ=1, MBS=1, the inner for-loops below will be totally unrolled.
39: */
40: template<class Type,PetscInt BS,PetscInt EQ>
41: __global__ static void d_Pack(PetscInt bs,PetscInt count,PetscInt start,const PetscInt *opt,const PetscInt *idx,const Type *data,Type *buf)
42: {
43: PetscInt i,s,t,tid = blockIdx.x*blockDim.x + threadIdx.x;
44: const PetscInt grid_size = gridDim.x * blockDim.x;
45: const PetscInt M = (EQ) ? 1 : bs/BS; /* If EQ, then M=1 enables compiler's const-propagation */
46: const PetscInt MBS = M*BS; /* MBS=bs. We turn MBS into a compile-time const when EQ=1. */
48: for (; tid<count; tid += grid_size) {
49: /* opt != NULL ==> idx == NULL, i.e., the indices have patterns but not contiguous;
50: opt == NULL && idx == NULL ==> the indices are contiguous;
51: */
52: t = (opt? MapTidToIndex(opt,tid) : (idx? idx[tid] : start+tid))*MBS;
53: s = tid*MBS;
54: for (i=0; i<MBS; i++) buf[s+i] = data[t+i];
55: }
56: }
58: template<class Type,class Op,PetscInt BS,PetscInt EQ>
59: __global__ static void d_UnpackAndOp(PetscInt bs,PetscInt count,PetscInt start,const PetscInt *opt,const PetscInt *idx,Type *data,const Type *buf)
60: {
61: PetscInt i,s,t,tid = blockIdx.x*blockDim.x + threadIdx.x;
62: const PetscInt grid_size = gridDim.x * blockDim.x;
63: const PetscInt M = (EQ) ? 1 : bs/BS, MBS = M*BS;
64: Op op;
66: for (; tid<count; tid += grid_size) {
67: t = (opt? MapTidToIndex(opt,tid) : (idx? idx[tid] : start+tid))*MBS;
68: s = tid*MBS;
69: for (i=0; i<MBS; i++) op(data[t+i],buf[s+i]);
70: }
71: }
73: template<class Type,class Op,PetscInt BS,PetscInt EQ>
74: __global__ static void d_FetchAndOp(PetscInt bs,PetscInt count,PetscInt rootstart,const PetscInt *rootopt,const PetscInt *rootidx,Type *rootdata,Type *leafbuf)
75: {
76: PetscInt i,l,r,tid = blockIdx.x*blockDim.x + threadIdx.x;
77: const PetscInt grid_size = gridDim.x * blockDim.x;
78: const PetscInt M = (EQ) ? 1 : bs/BS, MBS = M*BS;
79: Op op;
81: for (; tid<count; tid += grid_size) {
82: r = (rootopt? MapTidToIndex(rootopt,tid) : (rootidx? rootidx[tid] : rootstart+tid))*MBS;
83: l = tid*MBS;
84: for (i=0; i<MBS; i++) leafbuf[l+i] = op(rootdata[r+i],leafbuf[l+i]);
85: }
86: }
88: template<class Type,class Op,PetscInt BS,PetscInt EQ>
89: __global__ static void d_ScatterAndOp(PetscInt bs,PetscInt count,PetscInt srcx,PetscInt srcy,PetscInt srcX,PetscInt srcY,PetscInt srcStart,const PetscInt* srcIdx,const Type *src,PetscInt dstx,PetscInt dsty,PetscInt dstX,PetscInt dstY,PetscInt dstStart,const PetscInt *dstIdx,Type *dst)
90: {
91: PetscInt i,j,k,s,t,tid = blockIdx.x*blockDim.x + threadIdx.x;
92: const PetscInt grid_size = gridDim.x * blockDim.x;
93: const PetscInt M = (EQ) ? 1 : bs/BS, MBS = M*BS;
94: Op op;
96: for (; tid<count; tid += grid_size) {
97: if (!srcIdx) { /* src is either contiguous or 3D */
98: k = tid/(srcx*srcy);
99: j = (tid - k*srcx*srcy)/srcx;
100: i = tid - k*srcx*srcy - j*srcx;
101: s = srcStart + k*srcX*srcY + j*srcX + i;
102: } else {
103: s = srcIdx[tid];
104: }
106: if (!dstIdx) { /* dst is either contiguous or 3D */
107: k = tid/(dstx*dsty);
108: j = (tid - k*dstx*dsty)/dstx;
109: i = tid - k*dstx*dsty - j*dstx;
110: t = dstStart + k*dstX*dstY + j*dstX + i;
111: } else {
112: t = dstIdx[tid];
113: }
115: s *= MBS;
116: t *= MBS;
117: for (i=0; i<MBS; i++) op(dst[t+i],src[s+i]);
118: }
119: }
121: template<class Type,class Op,PetscInt BS,PetscInt EQ>
122: __global__ static void d_FetchAndOpLocal(PetscInt bs,PetscInt count,PetscInt rootstart,const PetscInt *rootopt,const PetscInt *rootidx,Type *rootdata,PetscInt leafstart,const PetscInt *leafopt,const PetscInt *leafidx,const Type *leafdata,Type *leafupdate)
123: {
124: PetscInt i,l,r,tid = blockIdx.x*blockDim.x + threadIdx.x;
125: const PetscInt grid_size = gridDim.x * blockDim.x;
126: const PetscInt M = (EQ) ? 1 : bs/BS, MBS = M*BS;
127: Op op;
129: for (; tid<count; tid += grid_size) {
130: r = (rootopt? MapTidToIndex(rootopt,tid) : (rootidx? rootidx[tid] : rootstart+tid))*MBS;
131: l = (leafopt? MapTidToIndex(leafopt,tid) : (leafidx? leafidx[tid] : leafstart+tid))*MBS;
132: for (i=0; i<MBS; i++) leafupdate[l+i] = op(rootdata[r+i],leafdata[l+i]);
133: }
134: }
136: /*====================================================================================*/
137: /* Regular operations on device */
138: /*====================================================================================*/
139: template<typename Type> struct Insert {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = y; return old;}};
140: template<typename Type> struct Add {__device__ Type operator() (Type& x,Type y) const {Type old = x; x += y; return old;}};
141: template<typename Type> struct Mult {__device__ Type operator() (Type& x,Type y) const {Type old = x; x *= y; return old;}};
142: template<typename Type> struct Min {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = PetscMin(x,y); return old;}};
143: template<typename Type> struct Max {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = PetscMax(x,y); return old;}};
144: template<typename Type> struct LAND {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = x && y; return old;}};
145: template<typename Type> struct LOR {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = x || y; return old;}};
146: template<typename Type> struct LXOR {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = !x != !y; return old;}};
147: template<typename Type> struct BAND {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = x & y; return old;}};
148: template<typename Type> struct BOR {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = x | y; return old;}};
149: template<typename Type> struct BXOR {__device__ Type operator() (Type& x,Type y) const {Type old = x; x = x ^ y; return old;}};
150: template<typename Type> struct Minloc {
151: __device__ Type operator() (Type& x,Type y) const {
152: Type old = x;
153: if (y.a < x.a) x = y;
154: else if (y.a == x.a) x.b = min(x.b,y.b);
155: return old;
156: }
157: };
158: template<typename Type> struct Maxloc {
159: __device__ Type operator() (Type& x,Type y) const {
160: Type old = x;
161: if (y.a > x.a) x = y;
162: else if (y.a == x.a) x.b = min(x.b,y.b); /* See MPI MAXLOC */
163: return old;
164: }
165: };
167: /*====================================================================================*/
168: /* Atomic operations on device */
169: /*====================================================================================*/
171: /*
172: Atomic Insert (exchange) operations
174: CUDA C Programming Guide V10.1 Chapter B.12.1.3:
176: int atomicExch(int* address, int val);
177: unsigned int atomicExch(unsigned int* address, unsigned int val);
178: unsigned long long int atomicExch(unsigned long long int* address, unsigned long long int val);
179: float atomicExch(float* address, float val);
181: reads the 32-bit or 64-bit word old located at the address address in global or shared
182: memory and stores val back to memory at the same address. These two operations are
183: performed in one atomic transaction. The function returns old.
185: PETSc notes:
187: It may be useful in PetscSFFetchAndOp with op = MPIU_REPLACE.
189: VecScatter with multiple entries scattered to the same location using INSERT_VALUES does not need
190: atomic insertion, since it does not need the old value. A 32-bit or 64-bit store instruction should
191: be atomic itself.
193: With bs>1 and a unit > 64 bits, the current element-wise atomic approach can not guarantee the whole
194: insertion is atomic. Hope no user codes rely on that.
195: */
196: __device__ static double atomicExch(double* address,double val) {return __longlong_as_double(atomicExch((unsigned long long int*)address,__double_as_longlong(val)));}
198: #if defined(PETSC_USE_64BIT_INDICES)
199: __device__ static PetscInt atomicExch(PetscInt* address,PetscInt val) {return (PetscInt)(atomicExch((unsigned long long int*)address,(unsigned long long int)val));}
200: #endif
202: template<typename Type> struct AtomicInsert {__device__ Type operator() (Type& x,Type y) const {return atomicExch(&x,y);}};
204: #if defined(PETSC_HAVE_COMPLEX)
205: #if defined(PETSC_USE_REAL_DOUBLE)
206: /* CUDA does not support 128-bit atomics. Users should not insert different 128-bit PetscComplex values to the same location */
207: template<> struct AtomicInsert<PetscComplex> {
208: __device__ PetscComplex operator() (PetscComplex& x,PetscComplex y) const {
209: PetscComplex old, *z = &old;
210: double *xp = (double*)&x,*yp = (double*)&y;
211: AtomicInsert<double> op;
212: z[0] = op(xp[0],yp[0]);
213: z[1] = op(xp[1],yp[1]);
214: return old; /* The returned value may not be atomic. It can be mix of two ops. Caller should discard it. */
215: }
216: };
217: #elif defined(PETSC_USE_REAL_SINGLE)
218: template<> struct AtomicInsert<PetscComplex> {
219: __device__ PetscComplex operator() (PetscComplex& x,PetscComplex y) const {
220: double *xp = (double*)&x,*yp = (double*)&y;
221: AtomicInsert<double> op;
222: return op(xp[0],yp[0]);
223: }
224: };
225: #endif
226: #endif
228: /*
229: Atomic add operations
231: CUDA C Programming Guide V10.1 Chapter B.12.1.1:
233: int atomicAdd(int* address, int val);
234: unsigned int atomicAdd(unsigned int* address,unsigned int val);
235: unsigned long long int atomicAdd(unsigned long long int* address,unsigned long long int val);
236: float atomicAdd(float* address, float val);
237: double atomicAdd(double* address, double val);
238: __half2 atomicAdd(__half2 *address, __half2 val);
239: __half atomicAdd(__half *address, __half val);
241: reads the 16-bit, 32-bit or 64-bit word old located at the address address in global or shared memory, computes (old + val),
242: and stores the result back to memory at the same address. These three operations are performed in one atomic transaction. The
243: function returns old.
245: The 32-bit floating-point version of atomicAdd() is only supported by devices of compute capability 2.x and higher.
246: The 64-bit floating-point version of atomicAdd() is only supported by devices of compute capability 6.x and higher.
247: The 32-bit __half2 floating-point version of atomicAdd() is only supported by devices of compute capability 6.x and
248: higher. The atomicity of the __half2 add operation is guaranteed separately for each of the two __half elements;
249: the entire __half2 is not guaranteed to be atomic as a single 32-bit access.
250: The 16-bit __half floating-point version of atomicAdd() is only supported by devices of compute capability 7.x and higher.
251: */
253: #if defined(PETSC_USE_64BIT_INDICES)
254: __device__ static PetscInt atomicAdd(PetscInt* address,PetscInt val) {return (PetscInt)atomicAdd((unsigned long long int*)address,(unsigned long long int)val);}
255: #endif
257: template<typename Type> struct AtomicAdd {__device__ Type operator() (Type& x,Type y) const {return atomicAdd(&x,y);}};
259: template<> struct AtomicAdd<double> {
260: __device__ double operator() (double& x,double y) const {
261: #if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 600)
262: return atomicAdd(&x,y);
263: #else
264: double *address = &x, val = y;
265: unsigned long long int *address_as_ull = (unsigned long long int*)address;
266: unsigned long long int old = *address_as_ull, assumed;
267: do {
268: assumed = old;
269: old = atomicCAS(address_as_ull, assumed, __double_as_longlong(val + __longlong_as_double(assumed)));
270: /* Note: uses integer comparison to avoid hang in case of NaN (since NaN !=NaN) */
271: } while (assumed != old);
272: return __longlong_as_double(old);
273: #endif
274: }
275: };
277: template<> struct AtomicAdd<float> {
278: __device__ float operator() (float& x,float y) const {
279: #if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 200)
280: return atomicAdd(&x,y);
281: #else
282: float *address = &x, val = y;
283: int *address_as_int = (int*)address;
284: int old = *address_as_int, assumed;
285: do {
286: assumed = old;
287: old = atomicCAS(address_as_int, assumed, __float_as_int(val + __int_as_float(assumed)));
288: /* Note: uses integer comparison to avoid hang in case of NaN (since NaN !=NaN) */
289: } while (assumed != old);
290: return __int_as_float(old);
291: #endif
292: }
293: };
295: #if defined(PETSC_HAVE_COMPLEX)
296: template<> struct AtomicAdd<PetscComplex> {
297: __device__ PetscComplex operator() (PetscComplex& x,PetscComplex y) const {
298: PetscComplex old, *z = &old;
299: PetscReal *xp = (PetscReal*)&x,*yp = (PetscReal*)&y;
300: AtomicAdd<PetscReal> op;
301: z[0] = op(xp[0],yp[0]);
302: z[1] = op(xp[1],yp[1]);
303: return old; /* The returned value may not be atomic. It can be mix of two ops. Caller should discard it. */
304: }
305: };
306: #endif
308: /*
309: Atomic Mult operations:
311: CUDA has no atomicMult at all, so we build our own with atomicCAS
312: */
313: #if defined(PETSC_USE_REAL_DOUBLE)
314: __device__ static double atomicMult(double* address, double val)
315: {
316: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
317: unsigned long long int old = *address_as_ull, assumed;
318: do {
319: assumed = old;
320: /* Other threads can access and modify value of *address_as_ull after the read above and before the write below */
321: old = atomicCAS(address_as_ull, assumed, __double_as_longlong(val*__longlong_as_double(assumed)));
322: } while (assumed != old);
323: return __longlong_as_double(old);
324: }
325: #elif defined(PETSC_USE_REAL_SINGLE)
326: __device__ static float atomicMult(float* address,float val)
327: {
328: int *address_as_int = (int*)(address);
329: int old = *address_as_int, assumed;
330: do {
331: assumed = old;
332: old = atomicCAS(address_as_int, assumed, __float_as_int(val*__int_as_float(assumed)));
333: } while (assumed != old);
334: return __int_as_float(old);
335: }
336: #endif
338: __device__ static int atomicMult(int* address,int val)
339: {
340: int *address_as_int = (int*)(address);
341: int old = *address_as_int, assumed;
342: do {
343: assumed = old;
344: old = atomicCAS(address_as_int, assumed, val*assumed);
345: } while (assumed != old);
346: return (int)old;
347: }
349: #if defined(PETSC_USE_64BIT_INDICES)
350: __device__ static int atomicMult(PetscInt* address,PetscInt val)
351: {
352: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
353: unsigned long long int old = *address_as_ull, assumed;
354: do {
355: assumed = old;
356: old = atomicCAS(address_as_ull, assumed, (unsigned long long int)(val*(PetscInt)assumed));
357: } while (assumed != old);
358: return (PetscInt)old;
359: }
360: #endif
362: template<typename Type> struct AtomicMult {__device__ Type operator() (Type& x,Type y) const {return atomicMult(&x,y);}};
364: /*
365: Atomic Min/Max operations
367: CUDA C Programming Guide V10.1 Chapter B.12.1.4~5:
369: int atomicMin(int* address, int val);
370: unsigned int atomicMin(unsigned int* address,unsigned int val);
371: unsigned long long int atomicMin(unsigned long long int* address,unsigned long long int val);
373: reads the 32-bit or 64-bit word old located at the address address in global or shared
374: memory, computes the minimum of old and val, and stores the result back to memory
375: at the same address. These three operations are performed in one atomic transaction.
376: The function returns old.
377: The 64-bit version of atomicMin() is only supported by devices of compute capability 3.5 and higher.
379: atomicMax() is similar.
380: */
382: #if defined(PETSC_USE_REAL_DOUBLE)
383: __device__ static double atomicMin(double* address, double val)
384: {
385: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
386: unsigned long long int old = *address_as_ull, assumed;
387: do {
388: assumed = old;
389: old = atomicCAS(address_as_ull, assumed, __double_as_longlong(PetscMin(val,__longlong_as_double(assumed))));
390: } while (assumed != old);
391: return __longlong_as_double(old);
392: }
394: __device__ static double atomicMax(double* address, double val)
395: {
396: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
397: unsigned long long int old = *address_as_ull, assumed;
398: do {
399: assumed = old;
400: old = atomicCAS(address_as_ull, assumed, __double_as_longlong(PetscMax(val,__longlong_as_double(assumed))));
401: } while (assumed != old);
402: return __longlong_as_double(old);
403: }
404: #elif defined(PETSC_USE_REAL_SINGLE)
405: __device__ static float atomicMin(float* address,float val)
406: {
407: int *address_as_int = (int*)(address);
408: int old = *address_as_int, assumed;
409: do {
410: assumed = old;
411: old = atomicCAS(address_as_int, assumed, __float_as_int(PetscMin(val,__int_as_float(assumed))));
412: } while (assumed != old);
413: return __int_as_float(old);
414: }
416: __device__ static float atomicMax(float* address,float val)
417: {
418: int *address_as_int = (int*)(address);
419: int old = *address_as_int, assumed;
420: do {
421: assumed = old;
422: old = atomicCAS(address_as_int, assumed, __float_as_int(PetscMax(val,__int_as_float(assumed))));
423: } while (assumed != old);
424: return __int_as_float(old);
425: }
426: #endif
428: /*
429: atomicMin/Max(long long *, long long) are not in Nvidia's documentation. But on OLCF Summit we found
430: atomicMin/Max/And/Or/Xor(long long *, long long) in /sw/summit/cuda/10.1.243/include/sm_32_atomic_functions.h.
431: This causes compilation errors with pgi compilers and 64-bit indices:
432: error: function "atomicMin(long long *, long long)" has already been defined
434: So we add extra conditions defined(__CUDA_ARCH__) && (__CUDA_ARCH__ < 320)
435: */
436: #if defined(PETSC_USE_64BIT_INDICES) && defined(__CUDA_ARCH__) && (__CUDA_ARCH__ < 320)
437: __device__ static PetscInt atomicMin(PetscInt* address,PetscInt val)
438: {
439: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
440: unsigned long long int old = *address_as_ull, assumed;
441: do {
442: assumed = old;
443: old = atomicCAS(address_as_ull, assumed, (unsigned long long int)(PetscMin(val,(PetscInt)assumed)));
444: } while (assumed != old);
445: return (PetscInt)old;
446: }
448: __device__ static PetscInt atomicMax(PetscInt* address,PetscInt val)
449: {
450: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
451: unsigned long long int old = *address_as_ull, assumed;
452: do {
453: assumed = old;
454: old = atomicCAS(address_as_ull, assumed, (unsigned long long int)(PetscMax(val,(PetscInt)assumed)));
455: } while (assumed != old);
456: return (PetscInt)old;
457: }
458: #endif
460: template<typename Type> struct AtomicMin {__device__ Type operator() (Type& x,Type y) const {return atomicMin(&x,y);}};
461: template<typename Type> struct AtomicMax {__device__ Type operator() (Type& x,Type y) const {return atomicMax(&x,y);}};
463: /*
464: Atomic bitwise operations
466: CUDA C Programming Guide V10.1 Chapter B.12.2.1 ~ B.12.2.3:
468: int atomicAnd(int* address, int val);
469: unsigned int atomicAnd(unsigned int* address,unsigned int val);
470: unsigned long long int atomicAnd(unsigned long long int* address,unsigned long long int val);
472: reads the 32-bit or 64-bit word old located at the address address in global or shared
473: memory, computes (old & val), and stores the result back to memory at the same
474: address. These three operations are performed in one atomic transaction.
475: The function returns old.
477: The 64-bit version of atomicAnd() is only supported by devices of compute capability 3.5 and higher.
479: atomicOr() and atomicXor are similar.
480: */
482: #if defined(PETSC_USE_64BIT_INDICES)
483: #if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ < 320) /* Why 320? see comments at atomicMin(PetscInt* address,PetscInt val) */
484: __device__ static PetscInt atomicAnd(PetscInt* address,PetscInt val)
485: {
486: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
487: unsigned long long int old = *address_as_ull, assumed;
488: do {
489: assumed = old;
490: old = atomicCAS(address_as_ull, assumed, (unsigned long long int)(val & (PetscInt)assumed));
491: } while (assumed != old);
492: return (PetscInt)old;
493: }
494: __device__ static PetscInt atomicOr(PetscInt* address,PetscInt val)
495: {
496: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
497: unsigned long long int old = *address_as_ull, assumed;
498: do {
499: assumed = old;
500: old = atomicCAS(address_as_ull, assumed, (unsigned long long int)(val | (PetscInt)assumed));
501: } while (assumed != old);
502: return (PetscInt)old;
503: }
505: __device__ static PetscInt atomicXor(PetscInt* address,PetscInt val)
506: {
507: unsigned long long int *address_as_ull = (unsigned long long int*)(address);
508: unsigned long long int old = *address_as_ull, assumed;
509: do {
510: assumed = old;
511: old = atomicCAS(address_as_ull, assumed, (unsigned long long int)(val ^ (PetscInt)assumed));
512: } while (assumed != old);
513: return (PetscInt)old;
514: }
515: #else
516: /*
517: See also comments at atomicMin(PetscInt* address,PetscInt val)
518: __device__ static PetscInt atomicAnd(PetscInt* address,PetscInt val) {return (PetscInt)atomicAnd((unsigned long long int*)address,(unsigned long long int)val);}
519: __device__ static PetscInt atomicOr (PetscInt* address,PetscInt val) {return (PetscInt)atomicOr ((unsigned long long int*)address,(unsigned long long int)val);}
520: __device__ static PetscInt atomicXor(PetscInt* address,PetscInt val) {return (PetscInt)atomicXor((unsigned long long int*)address,(unsigned long long int)val);}
521: */
522: #endif
523: #endif
525: template<typename Type> struct AtomicBAND {__device__ Type operator() (Type& x,Type y) const {return atomicAnd(&x,y);}};
526: template<typename Type> struct AtomicBOR {__device__ Type operator() (Type& x,Type y) const {return atomicOr (&x,y);}};
527: template<typename Type> struct AtomicBXOR {__device__ Type operator() (Type& x,Type y) const {return atomicXor(&x,y);}};
529: /*
530: Atomic logical operations:
532: CUDA has no atomic logical operations at all. We support them on integer types.
533: */
535: /* A template without definition makes any instantiation not using given specializations erroneous at compile time,
536: which is what we want since we only support 32-bit and 64-bit integers.
537: */
538: template<typename Type,class Op,int size/* sizeof(Type) */> struct AtomicLogical;
540: template<typename Type,class Op>
541: struct AtomicLogical<Type,Op,4> {
542: __device__ Type operator()(Type& x,Type y) const {
543: int *address_as_int = (int*)(&x);
544: int old = *address_as_int, assumed;
545: Op op;
546: do {
547: assumed = old;
548: old = atomicCAS(address_as_int, assumed, (int)(op((Type)assumed,y)));
549: } while (assumed != old);
550: return (Type)old;
551: }
552: };
554: template<typename Type,class Op>
555: struct AtomicLogical<Type,Op,8> {
556: __device__ Type operator()(Type& x,Type y) const {
557: unsigned long long int *address_as_ull = (unsigned long long int*)(&x);
558: unsigned long long int old = *address_as_ull, assumed;
559: Op op;
560: do {
561: assumed = old;
562: old = atomicCAS(address_as_ull, assumed, (unsigned long long int)(op((Type)assumed,y)));
563: } while (assumed != old);
564: return (Type)old;
565: }
566: };
568: /* Note land/lor/lxor below are different from LAND etc above. Here we pass arguments by value and return result of ops (not old value) */
569: template<typename Type> struct land {__device__ Type operator()(Type x, Type y) {return x && y;}};
570: template<typename Type> struct lor {__device__ Type operator()(Type x, Type y) {return x || y;}};
571: template<typename Type> struct lxor {__device__ Type operator()(Type x, Type y) {return (!x != !y);}};
573: template<typename Type> struct AtomicLAND {__device__ Type operator()(Type& x,Type y) const {AtomicLogical<Type,land<Type>,sizeof(Type)> op; return op(x,y);}};
574: template<typename Type> struct AtomicLOR {__device__ Type operator()(Type& x,Type y) const {AtomicLogical<Type,lor<Type> ,sizeof(Type)> op; return op(x,y);}};
575: template<typename Type> struct AtomicLXOR {__device__ Type operator()(Type& x,Type y) const {AtomicLogical<Type,lxor<Type>,sizeof(Type)> op; return op(x,y);}};
577: /*====================================================================================*/
578: /* Wrapper functions of cuda kernels. Function pointers are stored in 'link' */
579: /*====================================================================================*/
580: template<typename Type,PetscInt BS,PetscInt EQ>
581: static PetscErrorCode Pack(PetscSFLink link,PetscInt count,PetscInt start,PetscSFPackOpt opt,const PetscInt *idx,const void *data,void *buf)
582: {
583: cudaError_t cerr;
584: PetscInt nthreads=256;
585: PetscInt nblocks=(count+nthreads-1)/nthreads;
586: const PetscInt *iarray=opt ? opt->array : NULL;
589: if (!count) return(0);
590: nblocks = PetscMin(nblocks,link->maxResidentThreadsPerGPU/nthreads);
591: d_Pack<Type,BS,EQ><<<nblocks,nthreads,0,link->stream>>>(link->bs,count,start,iarray,idx,(const Type*)data,(Type*)buf);
592: cerr = cudaGetLastError();CHKERRCUDA(cerr);
593: return(0);
594: }
596: template<typename Type,class Op,PetscInt BS,PetscInt EQ>
597: static PetscErrorCode UnpackAndOp(PetscSFLink link,PetscInt count,PetscInt start,PetscSFPackOpt opt,const PetscInt *idx,void *data,const void *buf)
598: {
599: cudaError_t cerr;
600: PetscInt nthreads=256;
601: PetscInt nblocks=(count+nthreads-1)/nthreads;
602: const PetscInt *iarray=opt ? opt->array : NULL;
605: if (!count) return(0);
606: nblocks = PetscMin(nblocks,link->maxResidentThreadsPerGPU/nthreads);
607: d_UnpackAndOp<Type,Op,BS,EQ><<<nblocks,nthreads,0,link->stream>>>(link->bs,count,start,iarray,idx,(Type*)data,(const Type*)buf);
608: cerr = cudaGetLastError();CHKERRCUDA(cerr);
609: return(0);
610: }
612: template<typename Type,class Op,PetscInt BS,PetscInt EQ>
613: static PetscErrorCode FetchAndOp(PetscSFLink link,PetscInt count,PetscInt start,PetscSFPackOpt opt,const PetscInt *idx,void *data,void *buf)
614: {
615: cudaError_t cerr;
616: PetscInt nthreads=256;
617: PetscInt nblocks=(count+nthreads-1)/nthreads;
618: const PetscInt *iarray=opt ? opt->array : NULL;
621: if (!count) return(0);
622: nblocks = PetscMin(nblocks,link->maxResidentThreadsPerGPU/nthreads);
623: d_FetchAndOp<Type,Op,BS,EQ><<<nblocks,nthreads,0,link->stream>>>(link->bs,count,start,iarray,idx,(Type*)data,(Type*)buf);
624: cerr = cudaGetLastError();CHKERRCUDA(cerr);
625: return(0);
626: }
628: template<typename Type,class Op,PetscInt BS,PetscInt EQ>
629: static PetscErrorCode ScatterAndOp(PetscSFLink link,PetscInt count,PetscInt srcStart,PetscSFPackOpt srcOpt,const PetscInt *srcIdx,const void *src,PetscInt dstStart,PetscSFPackOpt dstOpt,const PetscInt *dstIdx,void *dst)
630: {
631: cudaError_t cerr;
632: PetscInt nthreads=256;
633: PetscInt nblocks=(count+nthreads-1)/nthreads;
634: PetscInt srcx=0,srcy=0,srcX=0,srcY=0,dstx=0,dsty=0,dstX=0,dstY=0;
637: if (!count) return(0);
638: nblocks = PetscMin(nblocks,link->maxResidentThreadsPerGPU/nthreads);
640: /* The 3D shape of source subdomain may be different than that of the destination, which makes it difficult to use CUDA 3D grid and block */
641: if (srcOpt) {srcx = srcOpt->dx[0]; srcy = srcOpt->dy[0]; srcX = srcOpt->X[0]; srcY = srcOpt->Y[0]; srcStart = srcOpt->start[0]; srcIdx = NULL;}
642: else if (!srcIdx) {srcx = srcX = count; srcy = srcY = 1;}
644: if (dstOpt) {dstx = dstOpt->dx[0]; dsty = dstOpt->dy[0]; dstX = dstOpt->X[0]; dstY = dstOpt->Y[0]; dstStart = dstOpt->start[0]; dstIdx = NULL;}
645: else if (!dstIdx) {dstx = dstX = count; dsty = dstY = 1;}
647: d_ScatterAndOp<Type,Op,BS,EQ><<<nblocks,nthreads,0,link->stream>>>(link->bs,count,srcx,srcy,srcX,srcY,srcStart,srcIdx,(const Type*)src,dstx,dsty,dstX,dstY,dstStart,dstIdx,(Type*)dst);
648: cerr = cudaGetLastError();CHKERRCUDA(cerr);
649: return(0);
650: }
652: /* Specialization for Insert since we may use cudaMemcpyAsync */
653: template<typename Type,PetscInt BS,PetscInt EQ>
654: static PetscErrorCode ScatterAndInsert(PetscSFLink link,PetscInt count,PetscInt srcStart,PetscSFPackOpt srcOpt,const PetscInt *srcIdx,const void *src,PetscInt dstStart,PetscSFPackOpt dstOpt,const PetscInt *dstIdx,void *dst)
655: {
656: PetscErrorCode ierr;
657: cudaError_t cerr;
660: if (!count) return(0);
661: /*src and dst are contiguous */
662: if ((!srcOpt && !srcIdx) && (!dstOpt && !dstIdx) && src != dst) {
663: cerr = cudaMemcpyAsync((Type*)dst+dstStart*link->bs,(const Type*)src+srcStart*link->bs,count*link->unitbytes,cudaMemcpyDeviceToDevice,link->stream);CHKERRCUDA(cerr);
664: } else {
665: ScatterAndOp<Type,Insert<Type>,BS,EQ>(link,count,srcStart,srcOpt,srcIdx,src,dstStart,dstOpt,dstIdx,dst);
666: }
667: return(0);
668: }
670: template<typename Type,class Op,PetscInt BS,PetscInt EQ>
671: static PetscErrorCode FetchAndOpLocal(PetscSFLink link,PetscInt count,PetscInt rootstart,PetscSFPackOpt rootopt,const PetscInt *rootidx,void *rootdata,PetscInt leafstart,PetscSFPackOpt leafopt,const PetscInt *leafidx,const void *leafdata,void *leafupdate)
672: {
673: cudaError_t cerr;
674: PetscInt nthreads=256;
675: PetscInt nblocks=(count+nthreads-1)/nthreads;
676: const PetscInt *rarray = rootopt ? rootopt->array : NULL;
677: const PetscInt *larray = leafopt ? leafopt->array : NULL;
680: if (!count) return(0);
681: nblocks = PetscMin(nblocks,link->maxResidentThreadsPerGPU/nthreads);
682: d_FetchAndOpLocal<Type,Op,BS,EQ><<<nblocks,nthreads,0,link->stream>>>(link->bs,count,rootstart,rarray,rootidx,(Type*)rootdata,leafstart,larray,leafidx,(const Type*)leafdata,(Type*)leafupdate);
683: cerr = cudaGetLastError();CHKERRCUDA(cerr);
684: return(0);
685: }
687: /*====================================================================================*/
688: /* Init various types and instantiate pack/unpack function pointers */
689: /*====================================================================================*/
690: template<typename Type,PetscInt BS,PetscInt EQ>
691: static void PackInit_RealType(PetscSFLink link)
692: {
693: /* Pack/unpack for remote communication */
694: link->d_Pack = Pack<Type,BS,EQ>;
695: link->d_UnpackAndInsert = UnpackAndOp <Type,Insert<Type> ,BS,EQ>;
696: link->d_UnpackAndAdd = UnpackAndOp <Type,Add<Type> ,BS,EQ>;
697: link->d_UnpackAndMult = UnpackAndOp <Type,Mult<Type> ,BS,EQ>;
698: link->d_UnpackAndMin = UnpackAndOp <Type,Min<Type> ,BS,EQ>;
699: link->d_UnpackAndMax = UnpackAndOp <Type,Max<Type> ,BS,EQ>;
700: link->d_FetchAndAdd = FetchAndOp <Type,Add<Type> ,BS,EQ>;
702: /* Scatter for local communication */
703: link->d_ScatterAndInsert = ScatterAndInsert<Type ,BS,EQ>; /* Has special optimizations */
704: link->d_ScatterAndAdd = ScatterAndOp <Type,Add<Type> ,BS,EQ>;
705: link->d_ScatterAndMult = ScatterAndOp <Type,Mult<Type> ,BS,EQ>;
706: link->d_ScatterAndMin = ScatterAndOp <Type,Min<Type> ,BS,EQ>;
707: link->d_ScatterAndMax = ScatterAndOp <Type,Max<Type> ,BS,EQ>;
708: link->d_FetchAndAddLocal = FetchAndOpLocal <Type,Add <Type> ,BS,EQ>;
710: /* Atomic versions when there are data-race possibilities */
711: link->da_UnpackAndInsert = UnpackAndOp <Type,AtomicInsert<Type>,BS,EQ>;
712: link->da_UnpackAndAdd = UnpackAndOp <Type,AtomicAdd<Type> ,BS,EQ>;
713: link->da_UnpackAndMult = UnpackAndOp <Type,AtomicMult<Type> ,BS,EQ>;
714: link->da_UnpackAndMin = UnpackAndOp <Type,AtomicMin<Type> ,BS,EQ>;
715: link->da_UnpackAndMax = UnpackAndOp <Type,AtomicMax<Type> ,BS,EQ>;
716: link->da_FetchAndAdd = FetchAndOp <Type,AtomicAdd<Type> ,BS,EQ>;
718: link->da_ScatterAndInsert = ScatterAndOp <Type,AtomicInsert<Type>,BS,EQ>;
719: link->da_ScatterAndAdd = ScatterAndOp <Type,AtomicAdd<Type> ,BS,EQ>;
720: link->da_ScatterAndMult = ScatterAndOp <Type,AtomicMult<Type> ,BS,EQ>;
721: link->da_ScatterAndMin = ScatterAndOp <Type,AtomicMin<Type> ,BS,EQ>;
722: link->da_ScatterAndMax = ScatterAndOp <Type,AtomicMax<Type> ,BS,EQ>;
723: link->da_FetchAndAddLocal = FetchAndOpLocal <Type,AtomicAdd<Type> ,BS,EQ>;
724: }
726: /* Have this templated class to specialize for char integers */
727: template<typename Type,PetscInt BS,PetscInt EQ,PetscInt size/*sizeof(Type)*/>
728: struct PackInit_IntegerType_Atomic {
729: static void Init(PetscSFLink link) {
730: link->da_UnpackAndInsert = UnpackAndOp<Type,AtomicInsert<Type>,BS,EQ>;
731: link->da_UnpackAndAdd = UnpackAndOp<Type,AtomicAdd<Type> ,BS,EQ>;
732: link->da_UnpackAndMult = UnpackAndOp<Type,AtomicMult<Type> ,BS,EQ>;
733: link->da_UnpackAndMin = UnpackAndOp<Type,AtomicMin<Type> ,BS,EQ>;
734: link->da_UnpackAndMax = UnpackAndOp<Type,AtomicMax<Type> ,BS,EQ>;
735: link->da_UnpackAndLAND = UnpackAndOp<Type,AtomicLAND<Type> ,BS,EQ>;
736: link->da_UnpackAndLOR = UnpackAndOp<Type,AtomicLOR<Type> ,BS,EQ>;
737: link->da_UnpackAndLXOR = UnpackAndOp<Type,AtomicLXOR<Type> ,BS,EQ>;
738: link->da_UnpackAndBAND = UnpackAndOp<Type,AtomicBAND<Type> ,BS,EQ>;
739: link->da_UnpackAndBOR = UnpackAndOp<Type,AtomicBOR<Type> ,BS,EQ>;
740: link->da_UnpackAndBXOR = UnpackAndOp<Type,AtomicBXOR<Type> ,BS,EQ>;
741: link->da_FetchAndAdd = FetchAndOp <Type,AtomicAdd<Type> ,BS,EQ>;
743: link->da_ScatterAndInsert = ScatterAndOp<Type,AtomicInsert<Type>,BS,EQ>;
744: link->da_ScatterAndAdd = ScatterAndOp<Type,AtomicAdd<Type> ,BS,EQ>;
745: link->da_ScatterAndMult = ScatterAndOp<Type,AtomicMult<Type> ,BS,EQ>;
746: link->da_ScatterAndMin = ScatterAndOp<Type,AtomicMin<Type> ,BS,EQ>;
747: link->da_ScatterAndMax = ScatterAndOp<Type,AtomicMax<Type> ,BS,EQ>;
748: link->da_ScatterAndLAND = ScatterAndOp<Type,AtomicLAND<Type> ,BS,EQ>;
749: link->da_ScatterAndLOR = ScatterAndOp<Type,AtomicLOR<Type> ,BS,EQ>;
750: link->da_ScatterAndLXOR = ScatterAndOp<Type,AtomicLXOR<Type> ,BS,EQ>;
751: link->da_ScatterAndBAND = ScatterAndOp<Type,AtomicBAND<Type> ,BS,EQ>;
752: link->da_ScatterAndBOR = ScatterAndOp<Type,AtomicBOR<Type> ,BS,EQ>;
753: link->da_ScatterAndBXOR = ScatterAndOp<Type,AtomicBXOR<Type> ,BS,EQ>;
754: link->da_FetchAndAddLocal = FetchAndOpLocal<Type,AtomicAdd<Type>,BS,EQ>;
755: }
756: };
758: /* CUDA does not support atomics on chars. It is TBD in PETSc. */
759: template<typename Type,PetscInt BS,PetscInt EQ>
760: struct PackInit_IntegerType_Atomic<Type,BS,EQ,1> {
761: static void Init(PetscSFLink link) {/* Nothing to leave function pointers NULL */}
762: };
764: template<typename Type,PetscInt BS,PetscInt EQ>
765: static void PackInit_IntegerType(PetscSFLink link)
766: {
767: link->d_Pack = Pack<Type,BS,EQ>;
768: link->d_UnpackAndInsert = UnpackAndOp<Type,Insert<Type>,BS,EQ>;
769: link->d_UnpackAndAdd = UnpackAndOp<Type,Add<Type> ,BS,EQ>;
770: link->d_UnpackAndMult = UnpackAndOp<Type,Mult<Type> ,BS,EQ>;
771: link->d_UnpackAndMin = UnpackAndOp<Type,Min<Type> ,BS,EQ>;
772: link->d_UnpackAndMax = UnpackAndOp<Type,Max<Type> ,BS,EQ>;
773: link->d_UnpackAndLAND = UnpackAndOp<Type,LAND<Type> ,BS,EQ>;
774: link->d_UnpackAndLOR = UnpackAndOp<Type,LOR<Type> ,BS,EQ>;
775: link->d_UnpackAndLXOR = UnpackAndOp<Type,LXOR<Type> ,BS,EQ>;
776: link->d_UnpackAndBAND = UnpackAndOp<Type,BAND<Type> ,BS,EQ>;
777: link->d_UnpackAndBOR = UnpackAndOp<Type,BOR<Type> ,BS,EQ>;
778: link->d_UnpackAndBXOR = UnpackAndOp<Type,BXOR<Type> ,BS,EQ>;
779: link->d_FetchAndAdd = FetchAndOp <Type,Add<Type> ,BS,EQ>;
781: link->d_ScatterAndInsert = ScatterAndInsert<Type,BS,EQ>;
782: link->d_ScatterAndAdd = ScatterAndOp<Type,Add<Type> ,BS,EQ>;
783: link->d_ScatterAndMult = ScatterAndOp<Type,Mult<Type> ,BS,EQ>;
784: link->d_ScatterAndMin = ScatterAndOp<Type,Min<Type> ,BS,EQ>;
785: link->d_ScatterAndMax = ScatterAndOp<Type,Max<Type> ,BS,EQ>;
786: link->d_ScatterAndLAND = ScatterAndOp<Type,LAND<Type> ,BS,EQ>;
787: link->d_ScatterAndLOR = ScatterAndOp<Type,LOR<Type> ,BS,EQ>;
788: link->d_ScatterAndLXOR = ScatterAndOp<Type,LXOR<Type> ,BS,EQ>;
789: link->d_ScatterAndBAND = ScatterAndOp<Type,BAND<Type> ,BS,EQ>;
790: link->d_ScatterAndBOR = ScatterAndOp<Type,BOR<Type> ,BS,EQ>;
791: link->d_ScatterAndBXOR = ScatterAndOp<Type,BXOR<Type> ,BS,EQ>;
792: link->d_FetchAndAddLocal = FetchAndOpLocal<Type,Add<Type>,BS,EQ>;
793: PackInit_IntegerType_Atomic<Type,BS,EQ,sizeof(Type)>::Init(link);
794: }
796: #if defined(PETSC_HAVE_COMPLEX)
797: template<typename Type,PetscInt BS,PetscInt EQ>
798: static void PackInit_ComplexType(PetscSFLink link)
799: {
800: link->d_Pack = Pack<Type,BS,EQ>;
801: link->d_UnpackAndInsert = UnpackAndOp<Type,Insert<Type>,BS,EQ>;
802: link->d_UnpackAndAdd = UnpackAndOp<Type,Add<Type> ,BS,EQ>;
803: link->d_UnpackAndMult = UnpackAndOp<Type,Mult<Type> ,BS,EQ>;
804: link->d_FetchAndAdd = FetchAndOp <Type,Add<Type> ,BS,EQ>;
806: link->d_ScatterAndInsert = ScatterAndInsert<Type,BS,EQ>;
807: link->d_ScatterAndAdd = ScatterAndOp<Type,Add<Type> ,BS,EQ>;
808: link->d_ScatterAndMult = ScatterAndOp<Type,Mult<Type> ,BS,EQ>;
809: link->d_FetchAndAddLocal = FetchAndOpLocal<Type,Add<Type>,BS,EQ>;
811: link->da_UnpackAndInsert = UnpackAndOp<Type,AtomicInsert<Type>,BS,EQ>;
812: link->da_UnpackAndAdd = UnpackAndOp<Type,AtomicAdd<Type>,BS,EQ>;
813: link->da_UnpackAndMult = NULL; /* Not implemented yet */
814: link->da_FetchAndAdd = NULL; /* Return value of atomicAdd on complex is not atomic */
816: link->da_ScatterAndInsert = ScatterAndOp<Type,AtomicInsert<Type>,BS,EQ>;
817: link->da_ScatterAndAdd = ScatterAndOp<Type,AtomicAdd<Type>,BS,EQ>;
818: }
819: #endif
821: typedef signed char SignedChar;
822: typedef unsigned char UnsignedChar;
823: typedef struct {int a; int b; } PairInt;
824: typedef struct {PetscInt a; PetscInt b;} PairPetscInt;
826: template<typename Type>
827: static void PackInit_PairType(PetscSFLink link)
828: {
829: link->d_Pack = Pack<Type,1,1>;
830: link->d_UnpackAndInsert = UnpackAndOp<Type,Insert<Type>,1,1>;
831: link->d_UnpackAndMaxloc = UnpackAndOp<Type,Maxloc<Type>,1,1>;
832: link->d_UnpackAndMinloc = UnpackAndOp<Type,Minloc<Type>,1,1>;
834: link->d_ScatterAndInsert = ScatterAndOp<Type,Insert<Type>,1,1>;
835: link->d_ScatterAndMaxloc = ScatterAndOp<Type,Maxloc<Type>,1,1>;
836: link->d_ScatterAndMinloc = ScatterAndOp<Type,Minloc<Type>,1,1>;
837: /* Atomics for pair types are not implemented yet */
838: }
840: template<typename Type,PetscInt BS,PetscInt EQ>
841: static void PackInit_DumbType(PetscSFLink link)
842: {
843: link->d_Pack = Pack<Type,BS,EQ>;
844: link->d_UnpackAndInsert = UnpackAndOp<Type,Insert<Type>,BS,EQ>;
845: link->d_ScatterAndInsert = ScatterAndInsert<Type,BS,EQ>;
846: /* Atomics for dumb types are not implemented yet */
847: }
849: /* Some device-specific utilities */
850: static PetscErrorCode PetscSFLinkSyncDevice_Cuda(PetscSFLink link)
851: {
852: cudaError_t cerr;
854: cerr = cudaDeviceSynchronize();CHKERRCUDA(cerr);
855: return(0);
856: }
858: static PetscErrorCode PetscSFLinkSyncStream_Cuda(PetscSFLink link)
859: {
860: cudaError_t cerr;
862: cerr = cudaStreamSynchronize(link->stream);CHKERRCUDA(cerr);
863: return(0);
864: }
866: static PetscErrorCode PetscSFLinkMemcpy_Cuda(PetscSFLink link,PetscMemType dstmtype,void* dst,PetscMemType srcmtype,const void*src,size_t n)
867: {
869: enum cudaMemcpyKind kinds[2][2] = {{cudaMemcpyHostToHost,cudaMemcpyHostToDevice},{cudaMemcpyDeviceToHost,cudaMemcpyDeviceToDevice}};
871: if (n) {
872: if (dstmtype == PETSC_MEMTYPE_HOST && srcmtype == PETSC_MEMTYPE_HOST) { /* Separate HostToHost so that pure-cpu code won't call cuda runtime */
873: PetscErrorCode PetscMemcpy(dst,src,n);
874: } else { /* Assume PETSC_MEMTYPE_HOST=0, PETSC_MEMTYPE_DEVICE=1 */
875: cudaError_t err = cudaMemcpyAsync(dst,src,n,kinds[srcmtype][dstmtype],link->stream);CHKERRCUDA(err);
876: }
877: }
878: return(0);
879: }
881: PetscErrorCode PetscSFMalloc_Cuda(PetscMemType mtype,size_t size,void** ptr)
882: {
884: if (mtype == PETSC_MEMTYPE_HOST) {PetscErrorCode PetscMalloc(size,ptr);}
885: else if (mtype == PETSC_MEMTYPE_DEVICE) {cudaError_t err = cudaMalloc(ptr,size);CHKERRCUDA(err);}
886: else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Wrong PetscMemType %d", (int)mtype);
887: return(0);
888: }
890: PetscErrorCode PetscSFFree_Cuda(PetscMemType mtype,void* ptr)
891: {
893: if (mtype == PETSC_MEMTYPE_HOST) {PetscErrorCode PetscFree(ptr);}
894: else if (mtype == PETSC_MEMTYPE_DEVICE) {cudaError_t err = cudaFree(ptr);CHKERRCUDA(err);}
895: else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Wrong PetscMemType %d",(int)mtype);
896: return(0);
897: }
899: /*====================================================================================*/
900: /* Main driver to init MPI datatype on device */
901: /*====================================================================================*/
903: /* Some fields of link are initialized by PetscSFPackSetUp_Host. This routine only does what needed on device */
904: PetscErrorCode PetscSFLinkSetUp_Cuda(PetscSF sf,PetscSFLink link,MPI_Datatype unit)
905: {
907: cudaError_t err;
908: PetscInt nSignedChar=0,nUnsignedChar=0,nInt=0,nPetscInt=0,nPetscReal=0;
909: PetscBool is2Int,is2PetscInt;
910: #if defined(PETSC_HAVE_COMPLEX)
911: PetscInt nPetscComplex=0;
912: #endif
915: if (link->deviceinited) return(0);
916: MPIPetsc_Type_compare_contig(unit,MPI_SIGNED_CHAR, &nSignedChar);
917: MPIPetsc_Type_compare_contig(unit,MPI_UNSIGNED_CHAR,&nUnsignedChar);
918: /* MPI_CHAR is treated below as a dumb type that does not support reduction according to MPI standard */
919: MPIPetsc_Type_compare_contig(unit,MPI_INT, &nInt);
920: MPIPetsc_Type_compare_contig(unit,MPIU_INT, &nPetscInt);
921: MPIPetsc_Type_compare_contig(unit,MPIU_REAL,&nPetscReal);
922: #if defined(PETSC_HAVE_COMPLEX)
923: MPIPetsc_Type_compare_contig(unit,MPIU_COMPLEX,&nPetscComplex);
924: #endif
925: MPIPetsc_Type_compare(unit,MPI_2INT,&is2Int);
926: MPIPetsc_Type_compare(unit,MPIU_2INT,&is2PetscInt);
928: if (is2Int) {
929: PackInit_PairType<PairInt>(link);
930: } else if (is2PetscInt) { /* TODO: when is2PetscInt and nPetscInt=2, we don't know which path to take. The two paths support different ops. */
931: PackInit_PairType<PairPetscInt>(link);
932: } else if (nPetscReal) {
933: if (nPetscReal == 8) PackInit_RealType<PetscReal,8,1>(link); else if (nPetscReal%8 == 0) PackInit_RealType<PetscReal,8,0>(link);
934: else if (nPetscReal == 4) PackInit_RealType<PetscReal,4,1>(link); else if (nPetscReal%4 == 0) PackInit_RealType<PetscReal,4,0>(link);
935: else if (nPetscReal == 2) PackInit_RealType<PetscReal,2,1>(link); else if (nPetscReal%2 == 0) PackInit_RealType<PetscReal,2,0>(link);
936: else if (nPetscReal == 1) PackInit_RealType<PetscReal,1,1>(link); else if (nPetscReal%1 == 0) PackInit_RealType<PetscReal,1,0>(link);
937: } else if (nPetscInt) {
938: if (nPetscInt == 8) PackInit_IntegerType<PetscInt,8,1>(link); else if (nPetscInt%8 == 0) PackInit_IntegerType<PetscInt,8,0>(link);
939: else if (nPetscInt == 4) PackInit_IntegerType<PetscInt,4,1>(link); else if (nPetscInt%4 == 0) PackInit_IntegerType<PetscInt,4,0>(link);
940: else if (nPetscInt == 2) PackInit_IntegerType<PetscInt,2,1>(link); else if (nPetscInt%2 == 0) PackInit_IntegerType<PetscInt,2,0>(link);
941: else if (nPetscInt == 1) PackInit_IntegerType<PetscInt,1,1>(link); else if (nPetscInt%1 == 0) PackInit_IntegerType<PetscInt,1,0>(link);
942: #if defined(PETSC_USE_64BIT_INDICES)
943: } else if (nInt) {
944: if (nInt == 8) PackInit_IntegerType<int,8,1>(link); else if (nInt%8 == 0) PackInit_IntegerType<int,8,0>(link);
945: else if (nInt == 4) PackInit_IntegerType<int,4,1>(link); else if (nInt%4 == 0) PackInit_IntegerType<int,4,0>(link);
946: else if (nInt == 2) PackInit_IntegerType<int,2,1>(link); else if (nInt%2 == 0) PackInit_IntegerType<int,2,0>(link);
947: else if (nInt == 1) PackInit_IntegerType<int,1,1>(link); else if (nInt%1 == 0) PackInit_IntegerType<int,1,0>(link);
948: #endif
949: } else if (nSignedChar) {
950: if (nSignedChar == 8) PackInit_IntegerType<SignedChar,8,1>(link); else if (nSignedChar%8 == 0) PackInit_IntegerType<SignedChar,8,0>(link);
951: else if (nSignedChar == 4) PackInit_IntegerType<SignedChar,4,1>(link); else if (nSignedChar%4 == 0) PackInit_IntegerType<SignedChar,4,0>(link);
952: else if (nSignedChar == 2) PackInit_IntegerType<SignedChar,2,1>(link); else if (nSignedChar%2 == 0) PackInit_IntegerType<SignedChar,2,0>(link);
953: else if (nSignedChar == 1) PackInit_IntegerType<SignedChar,1,1>(link); else if (nSignedChar%1 == 0) PackInit_IntegerType<SignedChar,1,0>(link);
954: } else if (nUnsignedChar) {
955: if (nUnsignedChar == 8) PackInit_IntegerType<UnsignedChar,8,1>(link); else if (nUnsignedChar%8 == 0) PackInit_IntegerType<UnsignedChar,8,0>(link);
956: else if (nUnsignedChar == 4) PackInit_IntegerType<UnsignedChar,4,1>(link); else if (nUnsignedChar%4 == 0) PackInit_IntegerType<UnsignedChar,4,0>(link);
957: else if (nUnsignedChar == 2) PackInit_IntegerType<UnsignedChar,2,1>(link); else if (nUnsignedChar%2 == 0) PackInit_IntegerType<UnsignedChar,2,0>(link);
958: else if (nUnsignedChar == 1) PackInit_IntegerType<UnsignedChar,1,1>(link); else if (nUnsignedChar%1 == 0) PackInit_IntegerType<UnsignedChar,1,0>(link);
959: #if defined(PETSC_HAVE_COMPLEX)
960: } else if (nPetscComplex) {
961: if (nPetscComplex == 8) PackInit_ComplexType<PetscComplex,8,1>(link); else if (nPetscComplex%8 == 0) PackInit_ComplexType<PetscComplex,8,0>(link);
962: else if (nPetscComplex == 4) PackInit_ComplexType<PetscComplex,4,1>(link); else if (nPetscComplex%4 == 0) PackInit_ComplexType<PetscComplex,4,0>(link);
963: else if (nPetscComplex == 2) PackInit_ComplexType<PetscComplex,2,1>(link); else if (nPetscComplex%2 == 0) PackInit_ComplexType<PetscComplex,2,0>(link);
964: else if (nPetscComplex == 1) PackInit_ComplexType<PetscComplex,1,1>(link); else if (nPetscComplex%1 == 0) PackInit_ComplexType<PetscComplex,1,0>(link);
965: #endif
966: } else {
967: MPI_Aint lb,nbyte;
968: MPI_Type_get_extent(unit,&lb,&nbyte);
969: if (lb != 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Datatype with nonzero lower bound %ld\n",(long)lb);
970: if (nbyte % sizeof(int)) { /* If the type size is not multiple of int */
971: if (nbyte == 4) PackInit_DumbType<char,4,1>(link); else if (nbyte%4 == 0) PackInit_DumbType<char,4,0>(link);
972: else if (nbyte == 2) PackInit_DumbType<char,2,1>(link); else if (nbyte%2 == 0) PackInit_DumbType<char,2,0>(link);
973: else if (nbyte == 1) PackInit_DumbType<char,1,1>(link); else if (nbyte%1 == 0) PackInit_DumbType<char,1,0>(link);
974: } else {
975: nInt = nbyte / sizeof(int);
976: if (nInt == 8) PackInit_DumbType<int,8,1>(link); else if (nInt%8 == 0) PackInit_DumbType<int,8,0>(link);
977: else if (nInt == 4) PackInit_DumbType<int,4,1>(link); else if (nInt%4 == 0) PackInit_DumbType<int,4,0>(link);
978: else if (nInt == 2) PackInit_DumbType<int,2,1>(link); else if (nInt%2 == 0) PackInit_DumbType<int,2,0>(link);
979: else if (nInt == 1) PackInit_DumbType<int,1,1>(link); else if (nInt%1 == 0) PackInit_DumbType<int,1,0>(link);
980: }
981: }
983: if (!sf->use_default_stream) {err = cudaStreamCreate(&link->stream);CHKERRCUDA(err);}
984: if (!sf->maxResidentThreadsPerGPU) { /* Not initialized */
985: int device;
986: struct cudaDeviceProp props;
987: err = cudaGetDevice(&device);CHKERRCUDA(err);
988: err = cudaGetDeviceProperties(&props,device);CHKERRCUDA(err);
989: sf->maxResidentThreadsPerGPU = props.maxThreadsPerMultiProcessor*props.multiProcessorCount;
990: }
991: link->maxResidentThreadsPerGPU = sf->maxResidentThreadsPerGPU;
993: link->d_SyncDevice = PetscSFLinkSyncDevice_Cuda;
994: link->d_SyncStream = PetscSFLinkSyncStream_Cuda;
995: link->Memcpy = PetscSFLinkMemcpy_Cuda;
996: link->deviceinited = PETSC_TRUE;
997: return(0);
998: }