Add option to change the local group size

Signed-off-by: Trivernis <trivernis@protonmail.com>

src/concurrency/executor.rs

@@ -18,6 +18,7 @@ impl ConcurrentKernelExecutor {
         &self,
         mut offset: u64,
         numbers_per_step: usize,
+        local_size: Option<usize>,
         stop: u64,
         no_cache: bool,
         num_threads: usize,
@@ -35,6 +36,7 @@ impl ConcurrentKernelExecutor {
             let controller = self.kernel_controller.clone();
             let offset = Arc::clone(&offset);
             let panic = Arc::clone(&panic);
+            let local_size = local_size.clone();
 
             handles.push(
                 ThreadBuilder::new()
@@ -54,7 +56,7 @@ impl ConcurrentKernelExecutor {
                             .collect::<Vec<u64>>();
                         let prime_result = if no_cache {
                             controller
-                                .filter_primes_simple(numbers)
+                                .filter_primes_simple(numbers, local_size.clone())
                                 .map_err(|e| {
                                     panic.store(true, Ordering::Relaxed);
                                     e
@@ -62,7 +64,7 @@ impl ConcurrentKernelExecutor {
                                 .unwrap()
                         } else {
                             controller
-                                .filter_primes(numbers)
+                                .filter_primes(numbers, local_size.clone())
                                 .map_err(|e| {
                                     panic.store(true, Ordering::Relaxed);
                                     e

src/kernel_controller/bench.rs

@@ -11,6 +11,7 @@ use std::time::{Duration, Instant};
 pub struct BenchStatistics {
     pub calc_count: u32,
     pub num_tasks: usize,
+    pub local_size: Option<usize>,
     pub write_duration: Duration,
     pub calc_duration: Duration,
     pub read_duration: Duration,
@@ -20,9 +21,10 @@ impl Display for BenchStatistics {
     fn fmt(&self, f: &mut Formatter<'_>) -> fmt::Result {
         write!(
             f,
-            "Calculation Count: {}\nTask Count: {}\nWrite Duration: {} ms\nGPU Duration: {} ms\nRead Duration: {} ms",
+            "Calculation Count: {}\nTask Count: {}\nLocal Size: {}\nWrite Duration: {} ms\nGPU Duration: {} ms\nRead Duration: {} ms",
             self.calc_count,
             self.num_tasks,
+            self.local_size.map(|v|v.to_string()).unwrap_or("n/a".to_string()),
             self.write_duration.as_secs_f64() * 1000f64,
             self.calc_duration.as_secs_f64() * 1000f64,
             self.read_duration.as_secs_f64() * 1000f64
@@ -40,7 +42,12 @@ impl BenchStatistics {
 
 impl KernelController {
     /// Benches an integer
-    pub fn bench_int(&self, calc_count: u32, num_tasks: usize) -> ocl::Result<BenchStatistics> {
+    pub fn bench_int(
+        &self,
+        calc_count: u32,
+        num_tasks: usize,
+        local_size: Option<usize>,
+    ) -> ocl::Result<BenchStatistics> {
         let write_start = Instant::now();
         let input_buffer = self
             .pro_que
@@ -50,9 +57,13 @@ impl KernelController {
             .build()?;
         let write_duration = write_start.elapsed();
 
-        let kernel = self
-            .pro_que
-            .kernel_builder("bench_int")
+        let mut builder = self.pro_que.kernel_builder("bench_int");
+
+        if let Some(local_size) = local_size {
+            builder.local_work_size(local_size);
+        }
+
+        let kernel = builder
             .arg(calc_count)
             .arg(&input_buffer)
             .global_work_size(num_tasks)
@@ -71,6 +82,7 @@ impl KernelController {
         Ok(BenchStatistics {
             num_tasks,
             calc_count,
+            local_size,
             read_duration,
             calc_duration,
             write_duration,

src/kernel_controller/mod.rs

@@ -6,7 +6,7 @@
 
 use ocl::core::DeviceInfo;
 use ocl::enums::DeviceInfoResult;
-use ocl::ProQue;
+use ocl::{CommandQueueProperties, ProQue};
 
 pub mod bench;
 pub mod primes;
@@ -21,12 +21,14 @@ impl KernelController {
         let pro_que = ProQue::builder()
             .src(include_str!("kernel.cl"))
             .dims(1 << 20)
+            .queue_properties(CommandQueueProperties::PROFILING_ENABLE)
             .build()?;
         println!("Using device {}", pro_que.device().name()?);
 
         Ok(Self { pro_que })
     }
 
+    /// Prints information about the gpu capabilities
     pub fn print_info(&self) -> ocl::Result<()> {
         let device = self.pro_que.device();
         let info_keys = vec![

src/kernel_controller/primes.rs

@@ -5,6 +5,8 @@
  */
 
 use crate::kernel_controller::KernelController;
+use ocl::core::{get_event_profiling_info, wait_for_event, ProfilingInfo};
+use ocl::EventList;
 use parking_lot::Mutex;
 use std::mem::size_of;
 use std::sync::Arc;
@@ -19,7 +21,11 @@ pub struct PrimeCalculationResult {
 impl KernelController {
     /// Filters all primes from the input without using a precalculated list of primes
     /// for divisibility checks
-    pub fn filter_primes_simple(&self, input: Vec<u64>) -> ocl::Result<PrimeCalculationResult> {
+    pub fn filter_primes_simple(
+        &self,
+        input: Vec<u64>,
+        local_size: Option<usize>,
+    ) -> ocl::Result<PrimeCalculationResult> {
         let input_buffer = self.pro_que.buffer_builder().len(input.len()).build()?;
         input_buffer.write(&input[..]).enq()?;
 
@@ -30,27 +36,37 @@ impl KernelController {
             .fill_val(0u8)
             .build()?;
 
-        let kernel = self
-            .pro_que
-            .kernel_builder("check_prime")
+        let mut builder = self.pro_que.kernel_builder("check_prime");
+        if let Some(local_size) = local_size {
+            builder.local_work_size(local_size);
+        }
+        let kernel = builder
             .arg(&input_buffer)
             .arg(&output_buffer)
             .global_work_size(input.len())
             .build()?;
 
-        let start = Instant::now();
+        let start_cpu = Instant::now();
+        let event_start = self.pro_que.queue().enqueue_marker::<EventList>(None)?;
+
         unsafe {
             kernel.enq()?;
         }
+        let event_stop = self.pro_que.queue().enqueue_marker::<EventList>(None)?;
+
+        wait_for_event(&event_start)?;
+        wait_for_event(&event_stop)?;
 
-        self.pro_que.finish()?;
-        let gpu_calc_duration = start.elapsed();
+        let start = get_event_profiling_info(&event_start, ProfilingInfo::End)?;
+        let stop = get_event_profiling_info(&event_stop, ProfilingInfo::Start)?;
+        let gpu_calc_duration = Duration::from_nanos(stop.time()? - start.time()?);
 
         let mut output = vec![0u8; output_buffer.len()];
         output_buffer.read(&mut output).enq()?;
         println!(
-            "GPU IO + Calculation took {} ms",
-            gpu_calc_duration.as_secs_f64() * 1000f64
+            "GPU Calculation: {} ms\nGPU IO + Calculation: {} ms",
+            gpu_calc_duration.as_secs_f64() * 1000f64,
+            start_cpu.elapsed().as_secs_f64() * 1000f64
         );
 
         let filter_start = Instant::now();
@@ -65,7 +81,11 @@ impl KernelController {
 
     /// Filters the primes from a list of numbers by using a precalculated list of primes to check
     /// for divisibility
-    pub fn filter_primes(&self, input: Vec<u64>) -> ocl::Result<PrimeCalculationResult> {
+    pub fn filter_primes(
+        &self,
+        input: Vec<u64>,
+        local_size: Option<usize>,
+    ) -> ocl::Result<PrimeCalculationResult> {
         lazy_static::lazy_static! {static ref PRIME_CACHE: Arc<Mutex<Vec<u64>>> = Arc::new(Mutex::new(Vec::new()));}
         if PRIME_CACHE.lock().len() == 0 {
             PRIME_CACHE.lock().append(&mut get_primes(
@@ -96,30 +116,41 @@ impl KernelController {
             .fill_val(0u8)
             .build()?;
 
-        let kernel = self
-            .pro_que
-            .kernel_builder("check_prime_cached")
+        let mut builder = self.pro_que.kernel_builder("check_prime_cached");
+        if let Some(local_size) = local_size {
+            builder.local_work_size(local_size);
+        }
+        let kernel = builder
             .arg(prime_buffer.len() as u32)
             .arg(&prime_buffer)
             .arg(&input_buffer)
             .arg(&output_buffer)
+            .local_work_size(2)
             .global_work_size(input.len())
             .build()?;
 
-        let start = Instant::now();
+        let event_start = self.pro_que.queue().enqueue_marker::<EventList>(None)?;
+        let start_cpu = Instant::now();
+
         unsafe {
             kernel.enq()?;
         }
+        let event_stop = self.pro_que.queue().enqueue_marker::<EventList>(None)?;
+
+        wait_for_event(&event_start)?;
+        wait_for_event(&event_stop)?;
 
-        self.pro_que.finish()?;
-        let gpu_calc_duration = start.elapsed();
+        let start = get_event_profiling_info(&event_start, ProfilingInfo::End)?;
+        let stop = get_event_profiling_info(&event_stop, ProfilingInfo::Start)?;
+        let gpu_calc_duration = Duration::from_nanos(stop.time()? - start.time()?);
 
         let mut output = vec![0u8; output_buffer.len()];
         output_buffer.read(&mut output).enq()?;
 
         println!(
-            "GPU IO + Calculation took {} ms",
-            gpu_calc_duration.as_secs_f64() * 1000f64
+            "GPU Calculation: {} ms\nGPU IO + Calculation: {} ms",
+            gpu_calc_duration.as_secs_f64() * 1000f64,
+            start_cpu.elapsed().as_secs_f64() * 1000f64
         );
 
         let prime_filter_start = Instant::now();

src/main.rs

@@ -55,6 +55,13 @@ struct CalculatePrimes {
     #[structopt(long = "timings-output", default_value = "timings.csv")]
     timings_file: PathBuf,
 
+    /// The local size for the tasks.
+    /// The value for numbers_per_step needs to be divisible by this number.
+    /// The maximum local size depends on the gpu capabilities.
+    /// If no value is provided, OpenCL chooses it automatically.
+    #[structopt(long = "local-size")]
+    local_size: Option<usize>,
+
     /// The amount of numbers that are checked per step. Even numbers are ignored so the
     /// Range actually goes to numbers_per_step * 2.
     #[structopt(long = "numbers-per-step", default_value = "33554432")]
@@ -83,6 +90,20 @@ struct BenchmarkTaskCount {
     #[structopt(long = "num-tasks-start", default_value = "1")]
     num_tasks_start: usize,
 
+    /// The initial number for the local size
+    #[structopt(long = "local-size-start")]
+    local_size_start: Option<usize>,
+
+    /// The amount the local size increases by every step
+    #[structopt(long = "local-size-step", default_value = "10")]
+    local_size_step: usize,
+
+    /// The maximum amount of the local size
+    /// Can't be greater than the maximum local size of the gpu
+    /// that can be retrieved with the info command
+    #[structopt(long = "local-size-stop")]
+    local_size_stop: Option<usize>,
+
     /// The maximum number of tasks for the benchmark
     #[structopt(long = "num-tasks-stop", default_value = "10000000")]
     num_tasks_stop: usize,
@@ -154,6 +175,7 @@ fn calculate_primes(prime_opts: CalculatePrimes, controller: KernelController) -
             executor.calculate_primes(
                 prime_opts.start_offset,
                 prime_opts.numbers_per_step,
+                prime_opts.local_size,
                 prime_opts.max_number,
                 prime_opts.no_cache,
                 prime_opts.num_threads,
@@ -205,6 +227,7 @@ fn bench_task_count(opts: BenchmarkTaskCount, controller: KernelController) -> o
     let csv_writer = CSVWriter::new(
         bench_writer,
         &[
+            "local_size",
             "num_tasks",
             "calc_count",
             "write_duration",
@@ -214,22 +237,45 @@ fn bench_task_count(opts: BenchmarkTaskCount, controller: KernelController) -> o
     )
     .unwrap();
     let (bench_sender, bench_handle) = create_csv_write_thread(csv_writer);
-    for n in (opts.num_tasks_start..opts.num_tasks_stop).step_by(opts.num_tasks_step) {
-        let mut stats = controller.bench_int(opts.calculation_steps, n)?;
-        for _ in 1..opts.average_of {
-            stats.avg(controller.bench_int(opts.calculation_steps, n)?)
+    for n in (opts.num_tasks_start..=opts.num_tasks_stop).step_by(opts.num_tasks_step) {
+        if let (Some(start), Some(stop)) = (opts.local_size_start, opts.local_size_stop) {
+            for l in (start..=stop)
+                .step_by(opts.local_size_step)
+                .filter(|v| n % v == 0)
+            {
+                let mut stats = controller.bench_int(opts.calculation_steps, n, Some(l))?;
+                for _ in 1..opts.average_of {
+                    stats.avg(controller.bench_int(opts.calculation_steps, n, Some(l))?)
+                }
+                println!("{}\n", stats);
+                bench_sender
+                    .send(vec![
+                        l.to_string(),
+                        n.to_string(),
+                        opts.calculation_steps.to_string(),
+                        duration_to_ms_string(&stats.write_duration),
+                        duration_to_ms_string(&stats.calc_duration),
+                        duration_to_ms_string(&stats.read_duration),
+                    ])
+                    .unwrap();
+            }
+        } else {
+            let mut stats = controller.bench_int(opts.calculation_steps, n, None)?;
+            for _ in 1..opts.average_of {
+                stats.avg(controller.bench_int(opts.calculation_steps, n, None)?)
+            }
+            println!("{}\n", stats);
+            bench_sender
+                .send(vec![
+                    "n/a".to_string(),
+                    n.to_string(),
+                    opts.calculation_steps.to_string(),
+                    duration_to_ms_string(&stats.write_duration),
+                    duration_to_ms_string(&stats.calc_duration),
+                    duration_to_ms_string(&stats.read_duration),
+                ])
+                .unwrap();
         }
-
-        println!("{}\n", stats);
-        bench_sender
-            .send(vec![
-                n.to_string(),
-                opts.calculation_steps.to_string(),
-                duration_to_ms_string(&stats.write_duration),
-                duration_to_ms_string(&stats.calc_duration),
-                duration_to_ms_string(&stats.read_duration),
-            ])
-            .unwrap();
     }
 
     mem::drop(bench_sender);